Swift Sampling is a training-free frame selection method that uses Taylor expansions on video latent trajectories to pick temporally surprising frames, outperforming uniform sampling on long-video QA tasks.
Bishop.Pattern Recognition and Machine Learning
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DNNs succeed by capturing high-order correlation structures in datasets, similar to mesoscale methods in physics.
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Swift Sampling: Selecting Temporal Surprises via Taylor Series
Swift Sampling is a training-free frame selection method that uses Taylor expansions on video latent trajectories to pick temporally surprising frames, outperforming uniform sampling on long-video QA tasks.
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DNNs, Dataset Statistics, and Correlation Functions
DNNs succeed by capturing high-order correlation structures in datasets, similar to mesoscale methods in physics.